To reach the above-mentioned goals, single-polarization and polarimetric models will be analyzed and/or developed to generate added-value products that consist of risk/vulnerability maps, targets at sea maps and pollutants maps, cyclone/typhoon monitoring. Typhoon monitoring will be addressed using a multi-sensor approach based on the exploitation of SAR, scatterometer and radiometer measurements. Hence, models to deal with extreme wind conditions will be analyzed/developed.

Oral presentation

Analysis of the SAR-derived Wind Signature over Extra-tropical Storm Conditions

The monitoring and forecasting of tropical and extra-tropical storm tracks and intensities are strategic for the protection of coastal infrastructures and residents. The Synthetic Aperture Radar (SAR) can potentially be very useful for such purposes. In fact, its high spatial resolution and its capability to observe the sea surface in all weather conditions and at all times (regardless of the day or night-time) makes it one of the best candidate instrument for these goals.

Several empirical forward models or geophysical model functions (GMFs), which relate the normalized radar backscatter cross section to the sea surface wind vector, have been developed and successfully used for a wide variety of scatterometer and SAR systems at different frequencies and polarizations. The GMFs have high accuracy under no-rain and low-to-moderate conditions, although for C-band radar systems good-quality winds are also derived under rainy conditions. For high wind speed measurements, the accuracy rapidly decreases due to saturation of the co-polarized backscattered intensity and the reduction of friction between the sea surface and the wind. An improved high-wind GMF for C-band and SAR spatial scales (most GMF developments are based on scatterometer data) as well as new high-wind GMFs for other frequencies (e.g., X-band) are required for the successful wind retrievals under tropical and extratropical cyclone conditions.

In this study, the radar backscatter sensitivity to high winds (as given by the different GMFs) is revisited for both C-band and X-band systems, as well as for co-polarized and cross-polarized beams, using the NOAA P-3 flight winter campaign data from January-February 2017. During this campaign, the NOAA P-3 plane, equipped with several sea-surface wind sensing systems, i.e., the Step Frequency Microwave Radiometer (SFMR), the Imaging Wind and Rain Profiler (IWRAP), and dropsondes, underflew both Sentinel-1 (S-1) and Cosmo-SkyMed (CSK) satellite passes under storm conditions in the North Atlantic region. These extra-tropical storms are characterized by vast areas of nearly uniform very high-wind conditions, up to 30-35 m/s. The sensitivity analysis will therefore provide a comprehensive view of the main sensitivities of the radar backscatter (e.g., co-polarized, cross-polarized, polarization difference, polarization ratio) to relatively high winds, for a variety of incidence angles.

Moreover, two wind retrieval approaches commonly used by the SAR community, i.e., the azimuth cut-off method and the combined radar backscatter and doppler centroid scheme, will be used to derive the sea surface wind field for the mentioned SAR scenes and validated against the mentioned NOAA wind data sources as well as collocated scatterometer and Soil Moisture Active Passive (SMAP) derived winds.

The amount of offshore platform is increasing significantly due to the improvements in drilling technology [1]. In particular, the advances due to deep water drilling technology allows installation to be mobile (to not have a stable location) and to be in regions far from coastal water.

Offshore platforms pose a risk to environment with the threat of oil and gas spillage, especially due to their exposition to extreme weather conditions. Besides being a risk to the environment, since their location is not mapped on maps, they are also obstacles for yachts, low flying airplanes and merchant ships in low visibility conditions.

Offshore platforms are generally large metallic constructions, which should make them easily detected and mapped by using satellite Synthetic Aperture Radar (SAR) medium resolution imagery [2]. However, we recently obtained analysed measurements [3] showing that some of the platforms in some acquisition geometries may be invisible in single-polarization backscattering images, leading to miss-detection. On the other hand the detection is still feasible if the dual polarimetric information is used.

In this work we exploiting a time series of dual-polarization TerraSAR-X data acquisitions over a cluster of offshore platform in the Gulf of Mexico. Among others, factors affecting the backscattering include polarization, resolution and incidence angle. Finally in this paper we also address how incoherent and coherent polarimetric observables can be exploited to detect platforms when the single polarimetric acquisition may fail detection.

The C-band synthetic aperture radar on-board ESA’s Sentinel satellites have the capability to provide high resolution wind vector information over the ocean surface. These wind vector data derived from SAR observations are available to the data assimilation system with real-time information of high accuracy. In this study, several comparison experiments are designed to investigate the impact of Sentinel-1 SAR winds data in the three-dimensional variational assimilation system for the Weather Research and Forecast model (WRF 3DVAR). The powerful Typhoon Lionrock is selected for this case study. Typhoon Lionrock struck and caused significant flooding and casualties in Japan and Russia in late August 2016. Its route changed several times and there are also several rapid intensification processes during its lifetime, which made its track very difficult to predict. Totally, 10 SAR images from 3 overpasses from August 27 to 29, 2016 are used in this study. The preliminary results demonstrate that SAR wind data can complement the scarce observations over the sea surface and improve the prediction of wind and pressure fields of Typhoon Lionrock. More detailed experimental results and analyses will be provided in the Dragon-4 symposium.

Coastal regions are rapidly growing with increase in urbanization and population density. This results in increasing threats for terrestrial habitats and marine ecosystems. Hence, ever growing attention must be paid to the pollution of the coastal waters fed from urban watersheds and human-related activities discharges. Pollutants include pesticided, fertilizers, hydrocarbons, trace of heavy metals, organic compounds, pathogens and other anthropogenic debris. They alter the physical and biogeochemical state of coastal waters affecting marine life negatively.

Stormwater and wastewater runoff are the main sources of pollution in coastal areas that result from untreated runoff and pollutants coming from urban watersheds entering the coastal waters after rainstorms, through river discharges or during publicly owned treatment works. They impact coastal water quality severely through an increase in bacterial contamination due to the significant load of particles and dissolved compounds discharged during and immediately after storm events.

The environmental observation of stormwater runoff in near-shore waters is commonly undertaken through sparse sampling onboard coastal research ships. Nonetheless, the information those field measuremets provide is sporadic, expensive and coarse. The space/time gap left by in-situ monitoring can be filled in by satellite measurements.

Satellite synthetic aperture radar (SAR)-based and ocean color imagery from Aqua MODIS have been used to analyze the different compounds of runoff plumes, surfactants and sediment discharge. Nevertheless, optical observations are limited by rainy events, cloud cover and solar illumination. In particular, polarimetric SAR (polSAR) represents the most suitable tool for monitoring the pollution of coastal waters due to the all-day and almost all-weather detailed information it provides on the scattering mechanisms of the observed scene routinely, with wide area coverage, dense revisit time and fine spatial resolution. The capability of polSARs to detect marine oil spills, to identify natural oil seepages and to roughly characterize the damping properties of surfactants was widely proved.

In this study, the sensitivity of polarimetric parameters derived from fully-polarimetric (FP) SAR measurements on the presence of surface pollutants in coastal waters is investigated. Preliminary results are obtained processing a set of FP SAR data collected at C-band from Radarsat-2 over the coastal area of Piana del Sele (Salerno, Italy). The test site was selected since it is one of the most industrialized areas of Southern Italy that is severely affected by coastal water pollution. Preliminary results show that polSAR data can be effectively used to retrive detailed information on the coastal water quality that may be useful for the sustainable development and managament of coastal areas, including marine ecosystems protection, aquacultures and fisheries safety, water resources management.

REFERENCES:

1) Holt, B, Trinh, R. and Gierach, M.M., 2017,

“Stormwater runoff plumes in the Southern California Bight: a comparison study with SAR and MODIS imagery”,

This study proposes a multi-sensor approach to promote an effective coastal area monitoring strategy over areas that include critical infrastructures, e.g. on-shore and off-shore oil/gas extraction platforms and groundwater reservoirs*. The monitoring strategy includes both land-side and sea-side observations using remotely sensed measurements.

With respect to the land-side, multi-temporal differential Interferometric Synthetic Aperture Radar (DInSAR) and Global Navigation Satellite System (GNSS) techniques are exploited to monitor subsidence phenomena along on-shore hydrocarbon and groundwater reservoirs, where surface deformations can be correlated to the extraction of resources from the subsoil.

With respect to the sea-side, effective SAR techniques are exploited to take benefit of multi-polarization SARs to observe oil/gas rigs/platforms and to observe oil discharges close to the oil extraction sites.

The proposed approach aims at testing and improving the standards of security for the exploitation of underground resources, as well as providing ad-hoc procedures to monitor interested areas.

*The present work is supported and funded both by Italian Economic Development Ministry (MISE) under the MISE-DGRME research project (ID 0752.010) and the DRAGON-4 Cooperation Proposal “SARCO - SAR-based Coast Observation” (ID 32235).

Many countries are focusing on maritime surveillance due to the interests in maritime shipping and the environment. The fact that more than eighty percent of goods traded worldwide are transported by sea is an indicator of the large amount of maritime traffic [1]. Not all the vessels uses the Automatic Identification System (AIS) [2], especially some smaller ships, and therefore they need to be monitored with independent systems. Therefore, using SAR data to detect ships has become more and more valuable.

Because of the complex structure of ships, their scattering mechanisms, which mainly consist of multiple reflections, are different from those of ocean surface [3]. These differences can be easily detected by using some polarimetric features. Compared with single-polarization backscattering images, dual- or quad-polarization images can provide more information about the scattering mechanisms composing the ships. This will therefore increase the discrimination between ships and ocean also in the case of ships where the overall amplitude is comparable to the one of the sea.

In this paper, we start from the Geometric Perturbation Polarimetric Notch Filter (GP-PNF) and extend the detector feature vector with many more polarimetric features [4-5]. Then we perform a Principal Component Analysis (PCA) to reduce the size of the vector and use this in the represent the full dataset in a new basis and use this basis to perform the PNF.

In our work, we choose some dual-polarization Sentinel-1 data as the experimental datasets. Experimental results show the effectiveness of the new method, especially in extreme weather conditions.

Satellite Earth Observation is of paramount importance for a wide range of applications. In fact, the synoptic view of the Earth offered by remotely sensed space-borne measurements allows gathering useful information on climate, environment, etc. Among those applications, the observation of oceans from space represents one of the key topics since oceans cover more than 70% of the Earth’s surface and they are responsible for life. In addition, monitoring the oceans makes us able to better understand natural and human-related processes as marine pollution, climate change, sea level rise, etc.

In this context the synthetic aperture radar (SAR), being a microwave active sensor, routinely provides, information on the Earth’s surface during day and nighttime and in almost any weather condition, with fine resolution and dense revisit time if virtual constellation are exploited.

In this study, European Space Agency (ESA) Sentinel-1 scanSAR Extra Wide Swath (EW) Ground Range Multilook Detected Medium Resolution (GRDM) dual-polarimetric (DP) VH-VV SAR data measurements are considered to extract information, at C-band, on hurricanes. The underpinning idea is to retrieve wind speed both with co-polar and with cross-polar channels. We used a Geophysical Model Function (GMF), the C-band Cross-Polarization Ocean (C-2PO) which is developed for cross-polarized channel and it is independent of incidence angle and wind direction, for the VH channel [1]. With respect to the VV channel, the azimuth cut-off method is studied to calculate a coefficient of linearity, that allows linking directly the azimuth cut-off with wind speed. The link between azimuth cut-off and wind speed is here investigated under extreme wind conditions.

The water-area variations of large lakes are affected by both long-term climate change and short-term localized human activities. In recent years, there has been increasing human activities in large inland lakes worldwide [1]. Within this context, remote sensing plays an important role for lake monitoring. Optical images have the great advantage of being simple to interpret and easily obtainable. However, optical radiation is severely affected by cloud cover, solar illumination, and other adverse meteorological conditions. These problems can be solved using radar sensors, which guarantee all-day and almost all-weather acquisitions, together with a wide area coverage. In particular, Synthetic Aperture Radar (SAR) can be very useful for lake monitoring purposes, because of its fine spatial resolution. Nevertheless, the monitoring using single-polarization SAR data is not simple due to both speckle noise, that makes image interpretability a challenge.

The main goals of this study are to develop multi polarimetric and multi-temporal methods to effectively monitor the change of surface water area of the dam of Monte Cotugno, Basilicata (Italy), the largest embankment dam in Europe. The test site was selected since it is one of the main civil strategic infrastructures of Southern Italy that is severely affected by seepage and leakage.

For this purpose, a method based on the joint use of co- and cross-polarized channels, is used in order to extract the profile of the artificial lake [2].

Preliminary results are obtained processing a set of dual polarimetric (DP) SAR data collected at C-band from Sentinel-1. The results show that Polarimetric SAR data can be effectively used to detect the changes of the water-level in the artificial lake.